Genetic Basis of Yellow Skin in Chickens Revealed by BCO2 Structural Variations

Genetic Basis of Yellow Skin in Chickens Revealed by BCO2 Structural Variations | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 11 August 2025 V1 Latest version Share on Genetic Basis of Yellow Skin in Chickens Revealed by BCO2 Structural Variations Authors : Li Rong , Xueying Wu , Jiao Li , Jiuhong Nan , Liubin Yang , Xuefeng Wang , and Shijun Li 0000-0001-9728-7949 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175490287.71488366/v1 264 views 149 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Chicken skin color is a classic Mendelian trait with significant economic importance, controlled by the W locus where white skin shows complete dominance over yellow skin. Although previous studies identified BCO2 (β,β-Carotene-9′,10′-dioxygenase) as the candidate gene underlying this phenotype, the precise functional mutation remains unknown, limiting practical breeding applications. Here, we conducted a comprehensive analysis combining GWAS (600K SNP array, n=381), transcriptomics, whole-genome sequencing (n=63), and comparative genomics. Candidate SVs were validated through allele-specific PCR genotyping in 148 individuals from seven populations. GWAS revealed a significant signal in the third intron of BCO2 (Chr24), while RNA-seq confirmed dramatically higher BCO2 expression in white-skinned chickens (log2FC=9.21, FDR=5.50e-129). While 287 SNPs/indels were identified in the extended BCO2 region, none showed perfect phenotypic association. Screening of structural variations (SVs) using high-quality genome assemblies identified four candidate SVs within BCO2. Validation in seven populations (n=148) demonstrated that two insertions (18-bp and 24-bp) exhibited perfect association with skin color phenotypes and codominant inheritance patterns. The identified 18bp and 24bp insertion variants within the BCO2 locus represent strong candidates for the causal mutations underlying chicken skin pigmentation. These SVs serve as direct, cost-effective PCR-based markers, overcoming limitations of SNP-based selection dependent on linkage disequilibrium. We propose that these insertions modulate BCO2 expression, leading to carotenoid degradation (white skin) or accumulation (yellow skin). Our findings provide molecular tools for marker-assisted selection and contribute to understanding the genetic basis of this economically important trait in poultry breeding. Genetic Basis of Yellow Skin in Chickens Revealed by BCO2 Structural Variations Li Rong 1 , Xueying Wu 1 , Jiao Li 1 , Jiuhong Nan 2 , Liubin Yang 1 , Xuefeng Wang 1 , Shijun Li 1,3,4 * 1 Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China. 2 The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou 311121, China 3 Key Laboratory of Smart Farming for Agricultural Animals, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China. 4 Hubei Hongshan Laboratory, Wuhan 430070, China. *Corresponding author: Shijun Li [email protected] ABSTRACT Chicken skin color is a classic Mendelian trait with significant economic importance, controlled by the W locus where white skin shows complete dominance over yellow skin. Although previous studies identified BCO2 (β,β-Carotene-9′,10′-dioxygenase) as the candidate gene underlying this phenotype, the precise functional mutation remains unknown, limiting practical breeding applications. Here, we conducted a comprehensive analysis combining GWAS (600K SNP array, n=381), transcriptomics, whole-genome sequencing (n=63), and comparative genomics. Candidate SVs were validated through allele-specific PCR genotyping in 148 individuals from seven populations. GWAS revealed a significant signal in the third intron of BCO2 (Chr24), while RNA-seq confirmed dramatically higher BCO2 expression in white-skinned chickens (log2FC=9.21, FDR=5.50e-129). While 287 SNPs/indels were identified in the extended BCO2 region, none showed perfect phenotypic association. Screening of structural variations (SVs) using high-quality genome assemblies identified four candidate SVs within BCO2. Validation in seven populations (n=148) demonstrated that two insertions (18-bp and 24-bp) exhibited perfect association with skin color phenotypes and codominant inheritance patterns. The identified 18bp and 24bp insertion variants within the BCO2 locus represent strong candidates for the causal mutations underlying chicken skin pigmentation. These SVs serve as direct, cost-effective PCR-based markers, overcoming limitations of SNP-based selection dependent on linkage disequilibrium. We propose that these insertions modulate BCO2 expression, leading to carotenoid degradation (white skin) or accumulation (yellow skin). Our findings provide molecular tools for marker-assisted selection and contribute to understanding the genetic basis of this economically important trait in poultry breeding. Keywords: BCO2 , Chicken skin color, GWAS, Structural variants, Molecular markers, Genetic mapping Chicken skin color varies significantly between populations, which has important implications for consumer preferences and market economics (Sirri et al. 2010; He et al. 2023). Early genetic studies established that the white skin phenotype is completely dominant over the yellow skin phenotype, following monogenic inheritance patterns (Bateson et al. 1909; W. et al. 1927). Subsequent work mapped this trait to the W locus, where the dominant W allele confers white skin through pigment degradation, while the recessive w allele permits carotenoid accumulation, resulting in yellow pigmentation (Zervas et al. 1962; Bhatnagar et al. 1972). Building on this classical framework, recent genomic advances have identified the molecular basis underlying this phenotypic variation. Eriksson et al. demonstrated that β,β-Carotene-9′,10′-dioxygenase ( BCO2 ) co-localizes with the classical W locus on chromosome 24 and shows significantly higher expression in white-skinned compared to yellow-skinned chickens (Eriksson et al. 2008). Mechanistically, BCO2 catalyzes the asymmetric cleavage of carotenoid substrates (lutein, zeaxanthin), converting pigmented xanthophylls into colorless apo-10′-carotenoids (Li et al. 2014; Dela Seña et al. 2016). This enzymatic activity explains how increased BCO2 expression leads to carotenoid depletion and the resulting white skin phenotype. Additionally, phylogenetic analyses suggest that yellow skin alleles introgressed from grey junglefowl into domestic chickens, indicating complex evolutionary origins of this trait (Eriksson et al. 2008; Zhao et al. 2024). Despite significant progress in characterizing BCO2 function and origin, the precise causal mutation remains unidentified, and practical molecular tools for routine breeding applications are still limited. Current studies have revealed SNP markers highly associated with skin color phenotypes (Jin et al. 2016; Wang et al. 2023). However, for monogenic traits like skin pigmentation, structural variations (SVs) may provide superior practical advantages over SNPs. Unlike SNPs, which serve as indirect markers dependent on linkage disequilibrium (LD) stability, SVs can exhibit co-dominant inheritance patterns and enable direct PCR-based genotyping without requiring high-throughput platforms (Alkan et al. 2011). This makes SVs particularly suitable for breeding applications where LD decay across populations often compromises SNP-based selection efficiency (Vos et al. 2017). Identifying the causal mutation would have significant practical implications. It would enable development of diagnostic markers for breeding programs, facilitate marker-assisted selection in diverse genetic backgrounds, and provide insights into the regulatory mechanisms controlling carotenoid metabolism in avian species. Therefore, this study aims to: (1) fine-map the causal region within the BCO2 locus using high-density genotyping, (2) identify SVs associated with skin color phenotypes, and (3) develop practical molecular markers for breeding applications. To identify genetic variants underlying chicken skin pigmentation, we performed a stepwise analysis beginning with mixed linear model (MLM)-based GWAS using 600K SNP data from 381 chickens, followed by transcriptome validation, whole-genome sequencing of 63 individuals across six populations, and structural variant screening using high-quality genome assemblies. The mapping population consisted of 381 individuals (247 yellow-skinned and 134 white-skinned), including 213 backcross family (BCF) progeny and 168 Jinghong (JH) parent hens (Table S1). The BCF was established by crossing one wild-type white-skinned rooster (local Chinese breed, WW) with 22 mutant yellow-skinned JH hens (ww), producing 29 first-generation hens of BCF that were subsequently backcrossed to the progenitor rooster to generate 213 second-generation offspring. All individuals were genotyped using a 600K SNP array (Aviagen Ltd., Midlothian, UK) (Kranis et al. 2013). To control for population stratification between second generation of BCF progeny and JH parental chickens, as well as potential sex-related effects, sex and the first five principal components (PCs) were included as covariates in the model, effectively minimizing false-positive associations arising from demographic confounding factors. To investigate the molecular mechanisms underlying skin pigmentation differences, tibial skin samples (including dermis and epidermis) were collected from three white-skinned Houdan (HD) chickens (WW) and three yellow-skinned White Leghorn (WLH) chickens (ww) for RNA sequencing (RNA-seq) analysis (Table S2). Differentially expressed genes (DEGs) were identified using stringent criteria of false discovery rate (FDR) < 0.01 and |log2 fold change| ≥ 1. To validate the RNA-seq findings, quantitative real-time PCR (qRT-PCR) was performed on BCO2 gene expression using skin samples from six WW HD and six ww WLH chickens, representing the same breeds used in the transcriptome analysis. To identify potential variants (SNPs/Indels) within the BCO2 gene region associated with skin pigmentation phenotypes, whole-genome sequencing (WGS) was performed on 63 individuals from six chicken populations (BCF; Grey Junglefowl, GJ; HD; JH; Wenchang,WC; WLH; detailed in Table S1). Variant screening was conducted using a two-step strategy: (1) targeted scanning of the BCO2 coding sequence (CDS); (2) an extended regional scan covering chromosome 24: 6,139,066–6,167,000 (GRCg6a, GCF_000002315.6), encompassing the entire BCO2 gene and the 23.8-kb linkage region previously reported by Eriksson et al. (Eriksson et al. 2008). To assess LD patterns within the extended region (chr24: 6,139,066–6,167,000; GRCg6a), we performed LD analysis using LDBlockShow software (Dong et al. 2021) with the “-SeleVar 2” parameter. Given the limitations of next-generation sequencing (NGS) in detecting SVs and the absence of perfect association variants from WGS point mutation analysis, we employed high-quality genome assemblies to systematically screen for SVs within the extended scanning region. Four genome assemblies were analyzed: yellow-skinned chickens (GRCg7w, GCF_016700215.2; and GRCg7b, GCF_016699485.2) and white-skinned chickens (GRCg6a; and Houdan, as reported by Li et al. 2022) (Li et al. 2022). Multiple sequence alignments were performed using the MUSCLE algorithm implemented in MEGA software (Tamura et al. 2021). This comparative analysis identified four candidate SVs exhibiting differential patterns between yellow-skinned and white-skinned chicken genome assemblies. To validate the phenotypic associations of these candidate SVs, allele-specific PCR genotyping was conducted on an expanded cohort of 148 individuals from seven chicken populations. Primer sequences targeting the four candidate SVs are provided in Table S3. To identify yellow skin-associated mutations, we conducted an MLM-based GWAS using 600K SNP array data from 381 chickens (247 yellow- vs. 134 white-skinned). To mitigate potential population stratification risks from sex and between the second generation of BCF and JH hens, we adjusted for sex and the top five PCs, which revealed a significant association signal on chromosome 24 (Fig. 1a), peaking in the third intron of BCO2 (transcript ID: XM_417929.6). To investigate the primary genes involved in the white and yellow skin phenotypes, RNA-seq of shank skin (comprising both dermis and epidermis) from 3 HD (WW) and 3 WLH(ww) identified 398 DEGs (Table S4). BCO2 showed the most significant differential expression (log2FC=9.21, FDR=5.50e-129) in white-skinned HD individuals (Fig. 1c). qRT-PCR analysis confirmed the RNA-seq results, showing consistent expression patterns for the BCO2 gene (log2FC=10.32, P=3.00e-4) (Fig. 1d). Subsequently, WGS data of 63 individuals from six populations (details in Table S1) was used to identify potential associated variations (SNPs/Indels) in BCO2 . Initially, we conducted a comprehensive scan of the CDS region and identified 9 SNPs (Table S5). However, none of these variants could effectively distinguish between yellow and white skin phenotypes (Table S6). Given this limitation, we expanded our scanning scope to encompass a broader genomic region (chr24:6,139,066–6,167,000; GRCg6a), which comprised the entire BCO2 gene and the 23.8-kb linkage region previously reported by Eriksson et al. (Eriksson et al. 2008) . This extended analysis revealed 287 genetic variations (Table S7). Despite the high degree of linkage disequilibrium observed among these variants (Fig S1), none of the identified variants could completely differentiate between the two phenotypes. Consequently, SVs screening was performed within the candidate region. Due to the inherent limitations of next-generation sequencing in accurately detecting SVs, we employed high-quality genome assemblies to systematically identify SVs within the expanded scanning region. This approach revealed 4 distinct SVs that exhibited differential patterns between the genome assemblies of yellow and white skin chicken breeds (Details of variant positions and nomenclature are provided in Table S8). To further validate the association between these four candidate SVs and skin pigmentation phenotypes, we performed allele-specific PCR genotyping of the four SVs across seven expanded populations (n=148, representative agarose gel images validating SVs are shown in Fig S2.). Genotyping analysis revealed that the 18 bp and 24 bp insertion variants achieved a frequency of 0.5 in the Wenshi-white population due to universal hemizygosity (Table 1). These insertions showed perfect discrimination between yellow-skinned and white-skinned individuals, while the 10 bp and 598 bp insertion variants demonstrated strong but incomplete phenotypic associations. Therefore, we propose to use 18 bp or 24 bp insertion variants as candidate SVs for causal mutations of chicken skin pigmentation and as reliable molecular markers for breeding programs. This study identified key SVs controlling chicken skin color by integrating GWAS, transcriptomics, and comparative genomics approaches, providing a molecular-level explanation for this classic Mendelian trait. The 18bp and 24bp insertion variants discovered within the BCO2 locus showed perfect association with skin pigmentation phenotypes, validating BCO2 as the molecular basis of the W locus. Compared to SNP markers, the identified SVs offer significant practical advantages for breeding applications, as these insertion variants display codominant inheritance patterns, enabling direct discrimination between homozygous and heterozygous genotypes. The PCR-based detection method is cost-effective and does not require high-throughput sequencing platforms. Crucially, as potential causal mutations, these SVs demonstrate superior stability across diverse populations without dependence on LD relationships (Alkan et al. 2011; Vos et al. 2017). Our transcriptome analysis confirmed significantly higher BCO2 expression in white-skinned individuals (log2FC=9.21), which is consistent with previous reports (Eriksson et al. 2008). We propose that the identified insertions regulate BCO2 expression in a dosage-dependent manner: homozygous insertions ( ww ) reduce enzymatic activity, promoting carotenoid accumulation, while the dominant W allele drives pigment cleavage through elevated BCO2 expression. This model explains how increased BCO2 expression leads to carotenoid degradation and the resulting white skin phenotype. The perfect phenotypic association of these variants makes them ideal diagnostic markers for early-stage phenotype prediction, improving selection efficiency, which addresses market demands for specific skin color preferences with significant economic implications (Sirri et al. 2010; He et al. 2023). Additionally, the 10bp and 598bp variants, showing strong but incomplete associations, suggest a complex mutational system that may synergistically regulate BCO2 function, and the interaction mechanisms among these variants warrant further investigation. These SVs also provide molecular markers for tracing gene introgression events during chicken domestication, particularly the introgression of yellow skin alleles from grey junglefowl into domestic chickens (Eriksson et al. 2008; Zhao et al. 2024). Although our study provides strong association evidence, functional validation through transgenic or gene editing experiments is necessary to confirm causal mechanisms, and validation in larger-scale and more diverse populations would strengthen the applicability of these markers across global chicken breeds. In conclusion, this study elucidated the molecular genetic basis of chicken skin color by identifying SVs within the BCO2 locus, providing precise molecular tools for modern poultry breeding that enable cost-effective, cross-population applicable genotyping technologies supporting marker-assisted selection and precision breeding to meet diverse market demands. ACKNOWLEDGMENTS This research was funded by the Major Project of Hubei Hongshan Laboratory (Project No. 2022hszd006); National Natural Science Foundation of China (grant no. 32372865) and the Major Program(JD)of Hubei Province(2023BAA029). CONFLICT OF INTEREST STATEMENT We have no conflicts of interest. DATA ACCESS All whole genome sequencing data are deposited in the Genome Sequence Archive (GSA: CRA020638; CRA020724) at https://ngdc.cncb.ac.cn/gsa. SNP-array data are available in OMIX (accession no.OMIX007999) at https://ngdc.cncb.ac.cn/omix (Chen et al. 2021; Memberspartners 2024). References 1. Alkan C., Coe B.P. & Eichler E.E. (2011) Genome structural variation discovery and genotyping. Nature Reviews Genetics 12, 363-76.2. Bateson W., Waunders E.R. & Punnett R.C. (1909) Experimental studies in the physiology of heredity. Molecular Genetics and Genomics 2, 17-9.3. Bhatnagar M.K., Reinhart B.S. & Jerome F.N. (1972) Inheritance of Plumage and Shank Color in Ring-necked Pheasants and Domestic Fowl Hybrids. Poultry Science 51, 911.4. Chen T., Chen X., Zhang S., Zhu J., Tang B., Wang A., Dong L., Zhang Z., Yu C., Sun Y., Chi L., Chen H., Zhai S., Sun Y., Lan L., Zhang X., Xiao J., Bao Y., Wang Y., Zhang Z. & Zhao W. (2021) The Genome Sequence Archive Family: Toward Explosive Data Growth and Diverse Data Types. Genomics Proteomics Bioinformatics 19, 578-83.5. Dela Seña C., Sun J., Narayanasamy S., Riedl K.M., Yuan Y., Curley R.W., Jr., Schwartz S.J. & Harrison E.H. (2016) Substrate Specificity of Purified Recombinant Chicken β-Carotene 9’,10’-Oxygenase (BCO2). J Biol Chem 291, 14609-19.6. Dong S.S., He W.M., Ji J.J., Zhang C., Guo Y. & Yang T.L. (2021) LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files. Brief Bioinform 22.7. Eriksson J., Larson G., Gunnarsson U., Bed’hom B., Tixier-Boichard M., Strömstedt L., Wright D., Jungerius A., Vereijken A., Randi E., Jensen P. & Andersson L. (2008) Identification of the yellow skin gene reveals a hybrid origin of the domestic chicken. PLoS Genet 4, e1000010.8. He S., Ren T., Lin W., Yang X., Hao T., Zhao G., Luo W., Nie Q. & Zhang X. (2023) Identification of candidate genes associated with skin yellowness in yellow chickens. Poult Sci 102, 102469.9. Jin S., Lee J.H., Seo D.W., Cahyadi M., Choi N.R., Heo K.N., Jo C. & Park H.B. (2016) A Major Locus for Quantitatively Measured Shank Skin Color Traits in Korean Native Chicken. Asian-Australas J Anim Sci 29, 1555-61.10. Kranis A., Gheyas A.A., Boschiero C., Turner F., Yu L., Smith S., Talbot R., Pirani A., Brew F., Kaiser P., Hocking P.M., Fife M., Salmon N., Fulton J., Strom T.M., Haberer G., Weigend S., Preisinger R., Gholami M., Qanbari S., Simianer H., Watson K.A., Woolliams J.A. & Burt D.W. (2013) Development of a high density 600K SNP genotyping array for chicken. BMC Genomics 14, 59.11. Li B., Vachali P.P., Gorusupudi A., Shen Z., Sharifzadeh H., Besch B.M., Nelson K., Horvath M.M., Frederick J.M., Baehr W. & Bernstein P.S. (2014) Inactivity of human β,β-carotene-9’,10’-dioxygenase (BCO2) underlies retinal accumulation of the human macular carotenoid pigment. Proc Natl Acad Sci U S A 111, 10173-8.12. Li M., Sun C., Xu N., Bian P., Tian X., Wang X., Wang Y., Jia X., Heller R., Wang M., Wang F., Dai X., Luo R., Guo Y., Wang X., Yang P., Hu D., Liu Z., Fu W., Zhang S., Li X., Wen C., Lan F., Siddiki A.Z., Suwannapoom C., Zhao X., Nie Q., Hu X., Jiang Y. & Yang N. (2022) De Novo Assembly of 20 Chicken Genomes Reveals the Undetectable Phenomenon for Thousands of Core Genes on Microchromosomes and Subtelomeric Regions. Mol Biol Evol 39.13. Memberspartners C.N. (2024) Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025. Nucleic Acids Research.14. Sirri F., Petracci M., Bianchi M. & Meluzzi A. (2010) Survey of skin pigmentation of yellow-skinned broiler chickens1. Poultry Science 89, 1556-61.15. Tamura K., Stecher G. & Kumar S. (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38, 3022-7.16. Vos P.G., Paulo M.J., Voorrips R.E., Visser R.G., van Eck H.J. & van Eeuwijk F.A. (2017) Evaluation of LD decay and various LD-decay estimators in simulated and SNP-array data of tetraploid potato. Theor Appl Genet 130, 123-35.17. W., V., LAMBERT, C., W. & KNOX (1927) Genetic Studies in Poultry: II. The Inheritance of Skin Color. Poultry Science 7, 24-30.18. Wang Y., Gan S., Luo C., Liu S., Ma J., Luo W., Lin C., Shu D. & Qu H. (2023) Variations in BCO2 Coding Sequence Causing a Difference in Carotenoid Concentration in the Skin of Chinese Indigenous Chicken. Genes 14, 671.19. Zervas N.P., Collins W.M. & Skoglund W.C. (1962) Genetic Variation and Covariation in Yellow Shank Pigmentation Intensity and 8 Week Body Weight of Chickens*. Poultry Science 41, 1247-54.20. Zhao X., Wen J., Zhang X., Zhang J., Zhu T., Wang H., Yang W., Cao G., Xiong W., Liu Y., Qu C., Ning Z. & Qu L. (2024) Significant genomic introgression from grey junglefowl (Gallus sonneratii) to domestic chickens (Gallus gallus domesticus). Journal of Animal Science and Biotechnology 15, 45. Fig. 1 Genetic mapping of yellow skin locus and gene expression analysis of yellow/white shank skin. a) GWAS of 600K SNPs in 381 chickens (247 yellow- vs 134 white-skinned) based on a mixed linear model. Chromosome-wide association peak at BCO2 locus. b) Corresponding QQ plot validating model assumptions. c) RNA-seq volcano plot comparing both phenotypes: horizontal axis (Log2FC) shows expression ratio of white vs. yellow skin; vertical axis (-log10(FDR)) indicates significance. Arrow highlights BCO2 as the most significant DEG. d) Relative BCO2 expression (n=12). ***P<0.001 via two-tailed t-test. Table 1 Allele frequency of 4 insertion variants in yellow and white skin chicken populations Yellow skin JH 24 1 1 1 1 WC 24 1 1 1 1 Yellow feather broilers 24 1 1 1 1 Hy-line Brown 24 1 1 1 1 Wenshi-yellow skin line 11 1 1 1 1 White skin Houdan 24 0 0 0 0 Wenshi-white skin line 17 0.6 0.5 0.5 0.6 Information & Authors Information Version history V1 Version 1 11 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords bco2 chicken skin color genetic mapping gwas molecular markers structural variants Authors Affiliations Li Rong Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Xueying Wu Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Jiao Li Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Jiuhong Nan The Second Affiliated Hospital of Zhejiang University School of Medicine Linping Campus View all articles by this author Liubin Yang Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Xuefeng Wang Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Shijun Li 0000-0001-9728-7949 [email protected] Huazhong Agriculture University Key Laboratory of Agricultural Animal Genetic Breeding and Reproduction of the Ministry of Education View all articles by this author Metrics & Citations Metrics Article Usage 264 views 149 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Li Rong, Xueying Wu, Jiao Li, et al. 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